Hilbert-Huang Transform with MATLAB Implementation
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Resource Overview
MATLAB code for Hilbert-Huang Transform featuring Empirical Mode Decomposition (EMD) implementation, thoroughly debugged and verified. Includes BMP output demonstrating runtime results. With parameter adjustments, enables multimodal decomposition for various signal types. Key features include signal sifting process, intrinsic mode function extraction, and instantaneous frequency analysis.
Detailed Documentation
This MATLAB implementation of Hilbert-Huang Transform focuses on the Empirical Mode Decomposition (EMD) component of HHT processing. The code has been extensively tested and successfully executes the complete EMD algorithm, which involves:
- Iterative sifting process to extract intrinsic mode functions (IMFs)
- Hilbert spectral analysis for time-frequency representation
- Boundary condition handling and stopping criterion implementation
The package includes runtime result demonstrations in BMP format showing the original signal, extracted IMFs, and Hilbert spectrum. By modifying input parameters such as sifting tolerance and maximum iterations, users can adapt the algorithm for multimodal decomposition of diverse signals including biomedical, seismic, and mechanical vibration data. This practical implementation serves as an educational tool for understanding non-stationary signal analysis through adaptive decomposition techniques.
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